
import copy
import os

import cva
import numpy as np
from matplotlib import pyplot as plt

class 							_UpperCamelCase					:






			'''simple docstring'''

			def __init__(							self			:							List[Any]   ):
							UpperCamelCase_:				Union[str, Any]						=    """"""
							UpperCamelCase_:				Dict						=    """"""
							UpperCamelCase_:				List[Any]						=    []
							UpperCamelCase_:				Union[str, Any]						=    0
							UpperCamelCase_:				List[str]						=    256
							UpperCamelCase_:				int						=    0
							UpperCamelCase_:				List[str]						=    0
							UpperCamelCase_:				Tuple						=    0
							UpperCamelCase_:				Optional[int]						=    0

			def    lowerCAmelCase__						(							self			:							Optional[int]    ,						snake_case_			:							List[Any]   ):
							UpperCamelCase_:				str						=    cva.imread(snake_case_    ,						0   )
							UpperCamelCase_:				Optional[Any]						=    copy.deepcopy(self.img   )
							UpperCamelCase_, UpperCamelCase_, UpperCamelCase_:				List[str]						=    plt.hist(self.img.ravel()    ,						256    ,						[0, 256]    ,						label="""x"""   )
							UpperCamelCase_:				List[str]						=    np.sum(snake_case_   )
							for i in range(len(snake_case_   )   ):
											UpperCamelCase_:				int						=    x[i] / self.k
											self.sk += prk
											UpperCamelCase_:				List[str]						=    (self.L - 1) * self.sk
											if self.rem != 0:
															UpperCamelCase_:				int						=    int(last % last   )
											UpperCamelCase_:				List[Any]						=    int(last + 1 if self.rem >= 0.5 else last   )
											self.last_list.append(snake_case_   )
											UpperCamelCase_:				Dict						=    int(np.ma.count(self.img   ) / self.img[1].size   )
											UpperCamelCase_:				int						=    self.img[1].size
							for i in range(self.number_of_cols   ):
											for j in range(self.number_of_rows   ):
															UpperCamelCase_:				List[Any]						=    self.img[j][i]
															if num != self.last_list[num]:
																			UpperCamelCase_:				List[Any]						=    self.last_list[num]
							cva.imwrite("""output_data/output.jpg"""    ,						self.img   )

			def    lowerCAmelCase__						(							self			:							Union[str, Any]   ):
							plt.hist(self.img.ravel()    ,						256    ,						[0, 256]   )




			def    lowerCAmelCase__						(							self			:							Any   ):
							cva.imshow("""Output-Image"""    ,						self.img   )
							cva.imshow("""Input-Image"""    ,						self.original_image   )
							cva.waitKey(5000   )
							cva.destroyAllWindows()


if __name__ == "__main__":
							lowerCamelCase_    :			List[Any]    =	os.path.join(os.path.basename(__file__), """image_data/input.jpg""")
							lowerCamelCase_    :			Optional[int]    =	ConstantStretch()
							stretcher.stretch(file_path)
							stretcher.plot_histogram()
							stretcher.show_image()








from ..utils import is_flax_available, is_torch_available


if is_torch_available():
							from .autoencoder_kl import AutoencoderKL
							from .controlnet import ControlNetModel
							from .dual_transformer_ad import DualTransformeraDModel
							from .modeling_utils import ModelMixin
							from .prior_transformer import PriorTransformer
							from .ta_film_transformer import TaFilmDecoder
							from .transformer_ad import TransformeraDModel
							from .unet_ad import UNetaDModel
							from .unet_ad import UNetaDModel
							from .unet_ad_condition import UNetaDConditionModel
							from .unet_ad_condition import UNetaDConditionModel
							from .vq_model import VQModel

if is_flax_available():
							from .controlnet_flax import FlaxControlNetModel
							from .unet_ad_condition_flax import FlaxUNetaDConditionModel
							from .vae_flax import FlaxAutoencoderKL






